• Static display
  • good for publication
  • effective to show very specific pattern
• Interactive display
  • gives end user more flexibility
  • exploratory visualization is convenient

install.packages(c("ggplot2","plotly", "DT", "gapminder"))

• gapminder data is used from gapminder package

library(gapminder)
dat <- subset(gapminder, year==2007)

library(ggplot2)
p <- ggplot(dat, aes(x = log(gdpPercap), y = lifeExp))+
  geom_point(aes(size = sqrt(pop/pi)), pch = 21, show.legend = FALSE) +
   scale_size_continuous(range=c(1,30)) + aes(fill = continent)
p

library(plotly)
ggplotly(p + aes(label = country))

q <- ggplot(gapminder, aes(x = log(gdpPercap), y = lifeExp, frame=year))+
  geom_point(aes(size = sqrt(pop/pi)), pch = 21, show.legend = FALSE) +
   scale_size_continuous(range=c(1,30)) + aes(fill = continent)
ggplotly(q + aes(label = country))

plot_ly(gapminder, x = ~gdpPercap, y = ~lifeExp, z = ~continent) %>%
  add_markers(color = ~continent)

library(leaflet)
leaflet() %>%
  addTiles() %>%  # use the default base map which is OpenStreetMap tiles
  addMarkers(lat = 41.257876, lng = -96.012557,
             popup = "University of Nebraska Omaha")

• Animation using ggplot2 and plotly